{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\fabio\Dropbox\Project EU Fiscal Policy\3 Bargaining outcomes\Sent to PSRM\third submission\Replication\figure_2.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 8 Feb 2021, 17:43:17
{txt}
{com}. 
. ***************** Replication of Franchino, Fabio, and Camilla Mariotto. “Bargaining Outcomes and Success in EU Economic Governance Reforms”. Political Science Research and Methods.
. 
. ***************** Figure 2
. version 16
{txt}
{com}. 
. use mad_NBSrp_noise.dta, clear
{txt}
{com}. 
. merge 1:1 v using mad_NBSnorp_noise.dta, nogen
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}               0
{txt}{col 5}matched{col 30}{res}              43{txt}  
{col 5}{hline 41}

{com}. merge 1:1 v using mad_comp_noise.dta, nogen
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}               0
{txt}{col 5}matched{col 30}{res}              43{txt}  
{col 5}{hline 41}

{com}. merge 1:1 v using mad_m_mean_noise.dta, nogen
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}               0
{txt}{col 5}matched{col 30}{res}              43{txt}  
{col 5}{hline 41}

{com}. merge 1:1 v using mad_minimax_noise.dta, nogen
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}               0
{txt}{col 5}matched{col 30}{res}              43{txt}  
{col 5}{hline 41}

{com}. merge 1:1 v using mad_PROCrp_noise.dta, nogen
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}               0
{txt}{col 5}matched{col 30}{res}              43{txt}  
{col 5}{hline 41}

{com}. merge 1:1 v using mad_PROCnorp_noise.dta, nogen
{res}
{txt}{col 5}Result{col 38}# of obs.
{col 5}{hline 41}
{col 5}not matched{col 30}{res}               0
{txt}{col 5}matched{col 30}{res}              43{txt}  
{col 5}{hline 41}

{com}. 
. sum comp m_mean NBSnorp PROCnorp minimax PROCrp NBSrp

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}comp {c |}{res}         43    21.08853    1.691673   18.45103   23.97114
{txt}{space 6}m_mean {c |}{res}         43    22.38325    1.293459   20.26174    24.5556
{txt}{space 5}NBSnorp {c |}{res}         43     22.7174     1.23388   20.75503   24.80171
{txt}{space 4}PROCnorp {c |}{res}         43    27.47402    4.174769   20.03911   33.93686
{txt}{space 5}minimax {c |}{res}         43    30.52723    .1779303   30.28511   30.75194
{txt}{hline 13}{c +}{hline 57}
{space 6}PROCrp {c |}{res}         43    34.57414    1.635122   31.45041   37.66398
{txt}{space 7}NBSrp {c |}{res}         43    42.62389    1.800859   39.81294   45.70923
{txt}
{com}. 
. eclplot PROCrp PROCrp_u PROCrp_l v, estopts(msize(tiny)) rplottype(rspike) ciopts(msize(small)) graphregion(fcolor(white)) xlabel(, labsize(2)) ylabel(, nogrid labsize(2)) title("PROC", size(2.5)) saving(PROCrp_noise, replace) xlabel(1 "1" 20 "20" 40 "40", labsize(2)) ylabel(25 "25" 50 "50", labsize(2)) xtitle("St.dev. of Gaussian noise", size(2)) ytitle("Mean absolute error", size(2))  text(50 1.1 "Min 31.5" "Max 37.5", size(2) place(se) just(left) box fc(white) margin(l+1 t+1 b+1) width(10))
{res}{txt}(file PROCrp_noise.gph saved)

{com}. 
. eclplot PROCnorp PROCnorp_u PROCnorp_l v, estopts(msize(tiny)) rplottype(rspike) ciopts(msize(small)) graphregion(fcolor(white)) xlabel(, labsize(2)) ylabel(, nogrid labsize(2)) title("PROC ¬ RP", size(2.5)) saving(PROCnorp_noise, replace) xlabel(1 "1" 20 "20" 40 "40", labsize(2)) ylabel(25 "25" 50 "50", labsize(2)) xtitle("St.dev. of Gaussian noise", size(2)) ytitle("Mean absolute error", size(2)) text(50 1.1 "Min 20" "Max 33.9", size(2) place(se) just(left) box fc(white) margin(l+1 t+1 b+1) width(10))
{res}{txt}(file PROCnorp_noise.gph saved)

{com}. 
. eclplot NBSrp NBSrp_u NBSrp_l v, estopts(msize(tiny)) rplottype(rspike) ciopts(msize(small)) graphregion(fcolor(white)) xlabel(, labsize(2)) ylabel(, nogrid labsize(2)) title("NBS", size(2.5)) saving(NBSrp_noise, replace) xlabel(1 "1" 20 "20" 40 "40", labsize(2)) ylabel(25 "25" 50 "50", labsize(2)) xtitle("St.dev. of Gaussian noise", size(2)) ytitle("Mean absolute error", size(2)) text(55 6 "Min 39.8" "Max 45.7", size(2) place(se) just(left) box fc(white) margin(l+1 t+1 b+1) width(10))
{res}{txt}(file NBSrp_noise.gph saved)

{com}. 
. eclplot NBSnorp NBSnorp_u NBSnorp_l v, estopts(msize(tiny)) rplottype(rspike) ciopts(msize(small)) graphregion(fcolor(white)) xlabel(, labsize(2)) ylabel(, nogrid labsize(2)) title("NBS ¬ RP", size(2.5)) saving(NBSnorp_noise, replace) xlabel(1 "1" 20 "20" 40 "40", labsize(2)) ylabel(25 "25" 50 "50", labsize(2)) xtitle("St.dev. of Gaussian noise", size(2)) ytitle("Mean absolute error", size(2)) text(50 1.1 "Min 20.8" "Max 24.8", size(2) place(se) just(left) box fc(white) margin(l+1 t+1 b+1) width(10))
{res}{txt}(file NBSnorp_noise.gph saved)

{com}. 
. eclplot comp comp_u comp_l v, estopts(msize(tiny)) rplottype(rspike) ciopts(msize(small)) graphregion(fcolor(white)) xlabel(, labsize(2)) ylabel(, nogrid labsize(2)) title("Compromise", size(2.5)) saving(comp_noise, replace) xlabel(1 "1" 20 "20" 40 "40", labsize(2)) ylabel(25 "25" 50 "50", labsize(2)) xtitle("St.dev. of Gaussian noise", size(2)) ytitle("Mean absolute error", size(2)) text(50 1.1 "Min 18.5" "Max 24", size(2) place(se) just(left) box fc(white) margin(l+1 t+1 b+1) width(10))
{res}{txt}(file comp_noise.gph saved)

{com}. 
. eclplot m_mean m_mean_u m_mean_l v, estopts(msize(tiny)) rplottype(rspike) ciopts(msize(small)) graphregion(fcolor(white)) xlabel(, labsize(2)) ylabel(, nogrid labsize(2)) title("Mean", size(2.5)) saving(mean_noise, replace) xlabel(1 "1" 20 "20" 40 "40", labsize(2)) ylabel(25 "25" 50 "50", labsize(2)) xtitle("St.dev. of Gaussian noise", size(2)) ytitle("Mean absolute error", size(2)) text(50 1.1 "Min 20.3" "Max 24.6", size(2) place(se) just(left) box fc(white) margin(l+1 t+1 b+1) width(10))
{res}{txt}(file mean_noise.gph saved)

{com}.  
. eclplot minimax minimax_u minimax_l v, estopts(msize(tiny)) rplottype(rspike) ciopts(msize(small)) graphregion(fcolor(white)) xlabel(, labsize(2)) ylabel(, nogrid labsize(2)) title("Minimax", size(2.5)) saving(minimax_noise, replace) xlabel(1 "1" 20 "20" 40 "40", labsize(2)) ylabel(25 "25" 50 "50", labsize(2)) xtitle("St.dev. of Gaussian noise", size(2)) ytitle("Mean absolute error", size(2)) text(50 1.1 "Min 30.3" "Max 30.8", size(2) place(se) just(left) box fc(white) margin(l+1 t+1 b+1) width(10))
{res}{txt}(file minimax_noise.gph saved)

{com}. 
. gr combine PROCrp_noise.gph PROCnorp_noise.gph NBSrp_noise.gph NBSnorp_noise.gph comp_noise.gph mean_noise.gph minimax_noise.gph, cols(2) graphregion(fcolor(white)) saving(figure_2_noise, replace) 
{res}{txt}(file figure_2_noise.gph saved)

{com}. 
. * computation for minimun, maximum and range values for each model
. * COMP
. sum comp

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 8}comp {c |}{res}         43    21.08853    1.691673   18.45103   23.97114
{txt}
{com}. matrix MN = r(min)
{txt}
{com}. matrix MX = r(max)
{txt}
{com}. matrix D = MX - MN
{txt}
{com}. matrix list D
{res}
{txt}symmetric D[1,1]
           c1
r1 {res} 5.5201149
{reset}
{com}. 
. * PROC ¬ RP
. sum PROCnorp

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 4}PROCnorp {c |}{res}         43    27.47402    4.174769   20.03911   33.93686
{txt}
{com}. matrix MN = r(min)
{txt}
{com}. matrix MX = r(max)
{txt}
{com}. matrix D = MX - MN
{txt}
{com}. matrix list D
{res}
{txt}symmetric D[1,1]
           c1
r1 {res} 13.897753
{reset}
{com}. 
. * mean
. sum m_mean

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}m_mean {c |}{res}         43    22.38325    1.293459   20.26174    24.5556
{txt}
{com}. matrix MN = r(min)
{txt}
{com}. matrix MX = r(max)
{txt}
{com}. matrix D = MX - MN
{txt}
{com}. matrix list D
{res}
{txt}symmetric D[1,1]
           c1
r1 {res} 4.2938557
{reset}
{com}. 
. * NBS ¬ RP
. sum NBSnorp

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}NBSnorp {c |}{res}         43     22.7174     1.23388   20.75503   24.80171
{txt}
{com}. matrix MN = r(min)
{txt}
{com}. matrix MX = r(max)
{txt}
{com}. matrix D = MX - MN
{txt}
{com}. matrix list D
{res}
{txt}symmetric D[1,1]
           c1
r1 {res} 4.0466862
{reset}
{com}. 
. * Minimax
. sum minimax

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 5}minimax {c |}{res}         43    30.52723    .1779303   30.28511   30.75194
{txt}
{com}. matrix MN = r(min)
{txt}
{com}. matrix MX = r(max)
{txt}
{com}. matrix D = MX - MN
{txt}
{com}. matrix list D
{res}
{txt}symmetric D[1,1]
          c1
r1 {res} .4668293
{reset}
{com}. 
. * PROC
. sum PROCrp

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 6}PROCrp {c |}{res}         43    34.57414    1.635122   31.45041   37.66398
{txt}
{com}. matrix MN = r(min)
{txt}
{com}. matrix MX = r(max)
{txt}
{com}. matrix D = MX - MN
{txt}
{com}. matrix list D
{res}
{txt}symmetric D[1,1]
           c1
r1 {res} 6.2135696
{reset}
{com}. 
. * NBS
. sum NBSrp

{txt}    Variable {c |}        Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 57}
{space 7}NBSrp {c |}{res}         43    42.62389    1.800859   39.81294   45.70923
{txt}
{com}. matrix MN = r(min)
{txt}
{com}. matrix MX = r(max)
{txt}
{com}. matrix D = MX - MN
{txt}
{com}. matrix list D
{res}
{txt}symmetric D[1,1]
          c1
r1 {res} 5.896286
{reset}
{com}. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\fabio\Dropbox\Project EU Fiscal Policy\3 Bargaining outcomes\Sent to PSRM\third submission\Replication\figure_2.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 8 Feb 2021, 17:43:28
{txt}{.-}
{smcl}
{txt}{sf}{ul off}